Examination of Situation-Dependent Background Error Covariances at the Convective Scale in the Context of the Ensemble Kalman Filter
Bibliographic record
Abstract
Abstract A high-resolution ensemble Kalman filter (HREnKF) system at the convective scale has been developed based on the Canadian Meteorological Center's operational global ensemble Kalman filter (EnKF) system. This study focuses on the very early stage of transition from purely homogeneous isotropic background error correlations to situation-dependent correlations. It has been found that forecast error structures can develop situation-dependent features in as little as 15 min. Furthermore, the dynamic and thermodynamic variables require different periods of time to build up their own forecast error structures. Differences in these structures between regions with and without precipitation are also investigated. An examination of temperature tendencies revealed that physical processes are as important as dynamical forcing in determining the structure of convective-scale errors structures, and that once physical processes become active, these structures change rapidly before the onset of precipitation. This study is intended to be the basis for a systematic exploration in the near future of the usefulness of the HREnKF system in assimilating high-density observations such as radar data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".